Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5763

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5763

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 by Noureddin Sadawi
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This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL5763 (TID: 101542), and it has 852 rows and 68 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent Molecular Descriptors which were generated from SMILES strings. Missing value imputation was applied to this dataset (By choosing the Median). Feature selection was also applied.

70 features

pXC50 (target)numeric655 unique values
0 missing
molecule_id (row identifier)nominal852 unique values
0 missing
C.028numeric5 unique values
0 missing
RBNnumeric23 unique values
0 missing
DLS_07numeric3 unique values
0 missing
ATSC2mnumeric741 unique values
0 missing
P_VSA_LogP_7numeric114 unique values
0 missing
nCsp3numeric28 unique values
0 missing
P_VSA_i_3numeric456 unique values
0 missing
CMC.80numeric2 unique values
0 missing
MSDnumeric679 unique values
0 missing
Infective.80numeric2 unique values
0 missing
P_VSA_s_5numeric17 unique values
0 missing
SpMin5_Bh.s.numeric384 unique values
0 missing
IC4numeric560 unique values
0 missing
Neoplastic.80numeric2 unique values
0 missing
SpMax1_Bh.e.numeric220 unique values
0 missing
SpMaxA_AEA.dm.numeric145 unique values
0 missing
IDEnumeric566 unique values
0 missing
LLS_02numeric6 unique values
0 missing
CENTnumeric644 unique values
0 missing
ATSC2vnumeric733 unique values
0 missing
P_VSA_MR_1numeric70 unique values
0 missing
SpMin5_Bh.m.numeric389 unique values
0 missing
SpMin5_Bh.v.numeric414 unique values
0 missing
NssNHnumeric5 unique values
0 missing
SpMin8_Bh.s.numeric402 unique values
0 missing
ATSC1vnumeric670 unique values
0 missing
MDDDnumeric712 unique values
0 missing
DLS_02numeric6 unique values
0 missing
SpMaxA_EA.ed.numeric270 unique values
0 missing
ATS3inumeric567 unique values
0 missing
Hypertens.80numeric2 unique values
0 missing
SpMin6_Bh.v.numeric431 unique values
0 missing
GATS2vnumeric354 unique values
0 missing
CATS2D_02_DLnumeric10 unique values
0 missing
Wapnumeric684 unique values
0 missing
ATS2inumeric528 unique values
0 missing
Sinumeric672 unique values
0 missing
Eta_Lnumeric760 unique values
0 missing
ISIZnumeric80 unique values
0 missing
nATnumeric80 unique values
0 missing
nHnumeric50 unique values
0 missing
nCsnumeric17 unique values
0 missing
nBTnumeric88 unique values
0 missing
GATS6vnumeric364 unique values
0 missing
MATS3pnumeric296 unique values
0 missing
GMTIVnumeric814 unique values
0 missing
ATSC1inumeric495 unique values
0 missing
SpMin1_Bh.e.numeric158 unique values
0 missing
ATSC3mnumeric803 unique values
0 missing
IVDEnumeric319 unique values
0 missing
SpMin6_Bh.p.numeric434 unique values
0 missing
SpMin6_Bh.e.numeric437 unique values
0 missing
SpMin6_Bh.i.numeric428 unique values
0 missing
VARnumeric258 unique values
0 missing
SpDiam_EA.ed.numeric257 unique values
0 missing
MATS3vnumeric312 unique values
0 missing
H.046numeric24 unique values
0 missing
ATS2enumeric534 unique values
0 missing
P_VSA_e_1numeric56 unique values
0 missing
P_VSA_m_1numeric55 unique values
0 missing
P_VSA_s_2numeric64 unique values
0 missing
P_VSA_v_1numeric55 unique values
0 missing
Eig01_AEA.ri.numeric232 unique values
0 missing
SpMax_AEA.ri.numeric232 unique values
0 missing
Eig01_EA.ed.numeric235 unique values
0 missing
SM10_AEA.dm.numeric235 unique values
0 missing
SpMax_EA.ed.numeric235 unique values
0 missing
Eig01_AEA.ed.numeric205 unique values
0 missing

62 properties

852
Number of instances (rows) of the dataset.
70
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
69
Number of numeric attributes.
1
Number of nominal attributes.
17103.16
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.39
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-1.99
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
1.01
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.01
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
187.33
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
0.66
Third quartile of kurtosis among attributes of the numeric type.
187197.12
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.57
Percentage of numeric attributes.
32.12
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-1.38
Minimum skewness among attributes of the numeric type.
1.43
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
0.03
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.66
Third quartile of skewness among attributes of the numeric type.
13.43
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.17
First quartile of kurtosis among attributes of the numeric type.
14.04
Third quartile of standard deviation of attributes of the numeric type.
1144259.27
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
1
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
3.53
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
3414.1
Mean of means among attributes of the numeric type.
-0.35
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.22
First quartile of standard deviation of attributes of the numeric type.
0.34
Average class difference between consecutive instances.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.
Entropy of the target attribute values.
Average number of distinct values among the attributes of the nominal type.
0.15
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.08
Number of attributes divided by the number of instances.
0.45
Mean skewness among attributes of the numeric type.
4.91
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.

12 tasks

2 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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